Struct aws_sdk_kinesisanalytics::operation::create_application::builders::CreateApplicationFluentBuilder

pub struct CreateApplicationFluentBuilder { /* private fields */ }

Fluent builder constructing a request to CreateApplication.

This documentation is for version 1 of the Amazon Kinesis Data Analytics API, which only supports SQL applications. Version 2 of the API supports SQL and Java applications. For more information about version 2, see Amazon Kinesis Data Analytics API V2 Documentation.

Creates an Amazon Kinesis Analytics application. You can configure each application with one streaming source as input, application code to process the input, and up to three destinations where you want Amazon Kinesis Analytics to write the output data from your application. For an overview, see How it Works.

In the input configuration, you map the streaming source to an in-application stream, which you can think of as a constantly updating table. In the mapping, you must provide a schema for the in-application stream and map each data column in the in-application stream to a data element in the streaming source.

Your application code is one or more SQL statements that read input data, transform it, and generate output. Your application code can create one or more SQL artifacts like SQL streams or pumps.

In the output configuration, you can configure the application to write data from in-application streams created in your applications to up to three destinations.

To read data from your source stream or write data to destination streams, Amazon Kinesis Analytics needs your permissions. You grant these permissions by creating IAM roles. This operation requires permissions to perform the kinesisanalytics:CreateApplication action.

For introductory exercises to create an Amazon Kinesis Analytics application, see Getting Started.

Implementations

impl CreateApplicationFluentBuilder

pub fn as_input(&self) -> &CreateApplicationInputBuilder

Access the CreateApplication as a reference.

pub async fn send( self ) -> Result<CreateApplicationOutput, SdkError<CreateApplicationError, HttpResponse>>

Sends the request and returns the response.

If an error occurs, an SdkError will be returned with additional details that can be matched against.

By default, any retryable failures will be retried twice. Retry behavior is configurable with the RetryConfig, which can be set when configuring the client.

pub fn customize( self ) -> CustomizableOperation<CreateApplicationOutput, CreateApplicationError, Self>

Consumes this builder, creating a customizable operation that can be modified before being sent.

pub fn application_name(self, input: impl Into<String>) -> Self

Name of your Amazon Kinesis Analytics application (for example, sample-app).

pub fn set_application_name(self, input: Option<String>) -> Self

Name of your Amazon Kinesis Analytics application (for example, sample-app).

pub fn get_application_name(&self) -> &Option<String>

Name of your Amazon Kinesis Analytics application (for example, sample-app).

pub fn application_description(self, input: impl Into<String>) -> Self

Summary description of the application.

pub fn set_application_description(self, input: Option<String>) -> Self

Summary description of the application.

pub fn get_application_description(&self) -> &Option<String>

Summary description of the application.

pub fn inputs(self, input: Input) -> Self

Appends an item to Inputs.

To override the contents of this collection use set_inputs.

Use this parameter to configure the application input.

You can configure your application to receive input from a single streaming source. In this configuration, you map this streaming source to an in-application stream that is created. Your application code can then query the in-application stream like a table (you can think of it as a constantly updating table).

For the streaming source, you provide its Amazon Resource Name (ARN) and format of data on the stream (for example, JSON, CSV, etc.). You also must provide an IAM role that Amazon Kinesis Analytics can assume to read this stream on your behalf.

To create the in-application stream, you need to specify a schema to transform your data into a schematized version used in SQL. In the schema, you provide the necessary mapping of the data elements in the streaming source to record columns in the in-app stream.

pub fn set_inputs(self, input: Option<Vec<Input>>) -> Self

Use this parameter to configure the application input.

You can configure your application to receive input from a single streaming source. In this configuration, you map this streaming source to an in-application stream that is created. Your application code can then query the in-application stream like a table (you can think of it as a constantly updating table).

For the streaming source, you provide its Amazon Resource Name (ARN) and format of data on the stream (for example, JSON, CSV, etc.). You also must provide an IAM role that Amazon Kinesis Analytics can assume to read this stream on your behalf.

To create the in-application stream, you need to specify a schema to transform your data into a schematized version used in SQL. In the schema, you provide the necessary mapping of the data elements in the streaming source to record columns in the in-app stream.

pub fn get_inputs(&self) -> &Option<Vec<Input>>

Use this parameter to configure the application input.

You can configure your application to receive input from a single streaming source. In this configuration, you map this streaming source to an in-application stream that is created. Your application code can then query the in-application stream like a table (you can think of it as a constantly updating table).

For the streaming source, you provide its Amazon Resource Name (ARN) and format of data on the stream (for example, JSON, CSV, etc.). You also must provide an IAM role that Amazon Kinesis Analytics can assume to read this stream on your behalf.

To create the in-application stream, you need to specify a schema to transform your data into a schematized version used in SQL. In the schema, you provide the necessary mapping of the data elements in the streaming source to record columns in the in-app stream.

pub fn outputs(self, input: Output) -> Self

Appends an item to Outputs.

To override the contents of this collection use set_outputs.

You can configure application output to write data from any of the in-application streams to up to three destinations.

These destinations can be Amazon Kinesis streams, Amazon Kinesis Firehose delivery streams, AWS Lambda destinations, or any combination of the three.

In the configuration, you specify the in-application stream name, the destination stream or Lambda function Amazon Resource Name (ARN), and the format to use when writing data. You must also provide an IAM role that Amazon Kinesis Analytics can assume to write to the destination stream or Lambda function on your behalf.

In the output configuration, you also provide the output stream or Lambda function ARN. For stream destinations, you provide the format of data in the stream (for example, JSON, CSV). You also must provide an IAM role that Amazon Kinesis Analytics can assume to write to the stream or Lambda function on your behalf.

pub fn set_outputs(self, input: Option<Vec<Output>>) -> Self

You can configure application output to write data from any of the in-application streams to up to three destinations.

These destinations can be Amazon Kinesis streams, Amazon Kinesis Firehose delivery streams, AWS Lambda destinations, or any combination of the three.

In the configuration, you specify the in-application stream name, the destination stream or Lambda function Amazon Resource Name (ARN), and the format to use when writing data. You must also provide an IAM role that Amazon Kinesis Analytics can assume to write to the destination stream or Lambda function on your behalf.

In the output configuration, you also provide the output stream or Lambda function ARN. For stream destinations, you provide the format of data in the stream (for example, JSON, CSV). You also must provide an IAM role that Amazon Kinesis Analytics can assume to write to the stream or Lambda function on your behalf.

pub fn get_outputs(&self) -> &Option<Vec<Output>>

You can configure application output to write data from any of the in-application streams to up to three destinations.

These destinations can be Amazon Kinesis streams, Amazon Kinesis Firehose delivery streams, AWS Lambda destinations, or any combination of the three.

In the configuration, you specify the in-application stream name, the destination stream or Lambda function Amazon Resource Name (ARN), and the format to use when writing data. You must also provide an IAM role that Amazon Kinesis Analytics can assume to write to the destination stream or Lambda function on your behalf.

In the output configuration, you also provide the output stream or Lambda function ARN. For stream destinations, you provide the format of data in the stream (for example, JSON, CSV). You also must provide an IAM role that Amazon Kinesis Analytics can assume to write to the stream or Lambda function on your behalf.

pub fn cloud_watch_logging_options(self, input: CloudWatchLoggingOption) -> Self

Appends an item to CloudWatchLoggingOptions.

To override the contents of this collection use set_cloud_watch_logging_options.

Use this parameter to configure a CloudWatch log stream to monitor application configuration errors. For more information, see Working with Amazon CloudWatch Logs.

pub fn set_cloud_watch_logging_options( self, input: Option<Vec<CloudWatchLoggingOption>> ) -> Self

Use this parameter to configure a CloudWatch log stream to monitor application configuration errors. For more information, see Working with Amazon CloudWatch Logs.

pub fn get_cloud_watch_logging_options( &self ) -> &Option<Vec<CloudWatchLoggingOption>>

Use this parameter to configure a CloudWatch log stream to monitor application configuration errors. For more information, see Working with Amazon CloudWatch Logs.

pub fn application_code(self, input: impl Into<String>) -> Self

One or more SQL statements that read input data, transform it, and generate output. For example, you can write a SQL statement that reads data from one in-application stream, generates a running average of the number of advertisement clicks by vendor, and insert resulting rows in another in-application stream using pumps. For more information about the typical pattern, see Application Code.

You can provide such series of SQL statements, where output of one statement can be used as the input for the next statement. You store intermediate results by creating in-application streams and pumps.

Note that the application code must create the streams with names specified in the Outputs. For example, if your Outputs defines output streams named ExampleOutputStream1 and ExampleOutputStream2, then your application code must create these streams.

pub fn set_application_code(self, input: Option<String>) -> Self

One or more SQL statements that read input data, transform it, and generate output. For example, you can write a SQL statement that reads data from one in-application stream, generates a running average of the number of advertisement clicks by vendor, and insert resulting rows in another in-application stream using pumps. For more information about the typical pattern, see Application Code.

You can provide such series of SQL statements, where output of one statement can be used as the input for the next statement. You store intermediate results by creating in-application streams and pumps.

Note that the application code must create the streams with names specified in the Outputs. For example, if your Outputs defines output streams named ExampleOutputStream1 and ExampleOutputStream2, then your application code must create these streams.

pub fn get_application_code(&self) -> &Option<String>

One or more SQL statements that read input data, transform it, and generate output. For example, you can write a SQL statement that reads data from one in-application stream, generates a running average of the number of advertisement clicks by vendor, and insert resulting rows in another in-application stream using pumps. For more information about the typical pattern, see Application Code.

You can provide such series of SQL statements, where output of one statement can be used as the input for the next statement. You store intermediate results by creating in-application streams and pumps.

Note that the application code must create the streams with names specified in the Outputs. For example, if your Outputs defines output streams named ExampleOutputStream1 and ExampleOutputStream2, then your application code must create these streams.

pub fn tags(self, input: Tag) -> Self

Appends an item to Tags.

To override the contents of this collection use set_tags.

A list of one or more tags to assign to the application. A tag is a key-value pair that identifies an application. Note that the maximum number of application tags includes system tags. The maximum number of user-defined application tags is 50. For more information, see Using Tagging.

pub fn set_tags(self, input: Option<Vec<Tag>>) -> Self

A list of one or more tags to assign to the application. A tag is a key-value pair that identifies an application. Note that the maximum number of application tags includes system tags. The maximum number of user-defined application tags is 50. For more information, see Using Tagging.

pub fn get_tags(&self) -> &Option<Vec<Tag>>

A list of one or more tags to assign to the application. A tag is a key-value pair that identifies an application. Note that the maximum number of application tags includes system tags. The maximum number of user-defined application tags is 50. For more information, see Using Tagging.

Trait Implementations

impl Clone for CreateApplicationFluentBuilder

fn clone(&self) -> CreateApplicationFluentBuilder

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for CreateApplicationFluentBuilder

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.